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Simple Python library written in Rust for analyzing and scoping out patterns in time series data

Project description

TimeScope

pypi license

Simple Python library written in Rust for analyzing and scoping out patterns in time series data. This is a pet project to practice programming in Rust and currently only contains two algorithms:

  • ED-Pelt change point detection
  • Steady State detection (based on change points)

Example Use

from timescope import TimeSeriesData, cpd_ed_pelt, ssd_cpd

A = [0, 0, 0, 0, 10, 10, 10, 10, 10, 0, 0, 0, 0]
B = list(range(len(A)))

cps = cpd_ed_pelt(A, 1)
print(f"change points: {cps}")
# change points: [4, 9]

ts = TimeSeriesData(B, A)
print(ts)
# TimeSeriesData(time=[0, 1, ..., 11, 12], data=[0, 0, ..., 0, 0], granularity=1, is_step=false)

resampled_ts = ts.equally_spaced_resampling()
print(resampled_ts.slice(3, 6))
# TimeSeriesData(time=[3, 4, 5, 6], data=[0, 10, 10, 10], granularity=1, is_step=false)

ss_map = ssd_cpd(resampled_ts, 1, 1.0, -1.0)
print(f"steady state map: {ss_map.data}")
# steady state map: [1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0]

Install

pip install timescope

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BLAKE2b-256 c7c962c3312c2768477298dee7838adb1792b3271837dde051c5e52ddd019022

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